OBO Foundry dashboard analysis¶

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/tmp/ipykernel_328/4293058459.py:21: FutureWarning:

The `inplace` parameter in pandas.Categorical.reorder_categories is deprecated and will be removed in a future version. Reordering categories will always return a new Categorical object.

Ontologies by number of axioms

Ontologies by number of classes

Ontologies by how many ontologies use it

Different serialisations used

RDF/XML Syntax    1
Name: syntax, dtype: int64

Breakdown of used Axiom Types

count mean std min 25% 50% 75% max
AnnotationAssertion 1 177.0 NaN 177.0 177.0 177.0 177.0 177.0
ClassAssertion 1 2.0 NaN 2.0 2.0 2.0 2.0 2.0
DataPropertyDomain 1 30.0 NaN 30.0 30.0 30.0 30.0 30.0
DataPropertyRange 1 31.0 NaN 31.0 31.0 31.0 31.0 31.0
Declaration 1 113.0 NaN 113.0 113.0 113.0 113.0 113.0
DisjointClasses 1 1.0 NaN 1.0 1.0 1.0 1.0 1.0
ObjectPropertyDomain 1 26.0 NaN 26.0 26.0 26.0 26.0 26.0
ObjectPropertyRange 1 29.0 NaN 29.0 29.0 29.0 29.0 29.0
SubClassOf 1 49.0 NaN 49.0 49.0 49.0 49.0 49.0

Breakdown of used OWL Class Expression constructs

count mean std min 25% 50% 75% max
Class 1 219.0 NaN 219.0 219.0 219.0 219.0 219.0
DataExactCardinality 1 14.0 NaN 14.0 14.0 14.0 14.0 14.0
ObjectAllValuesFrom 1 19.0 NaN 19.0 19.0 19.0 19.0 19.0
ObjectExactCardinality 1 15.0 NaN 15.0 15.0 15.0 15.0 15.0
ObjectIntersectionOf 1 19.0 NaN 19.0 19.0 19.0 19.0 19.0
ObjectMaxCardinality 1 2.0 NaN 2.0 2.0 2.0 2.0 2.0
ObjectSomeValuesFrom 1 11.0 NaN 11.0 11.0 11.0 11.0 11.0
ObjectUnionOf 1 5.0 NaN 5.0 5.0 5.0 5.0 5.0

OBO Score (Experimental)

ontology score score_dash score_impact
0 MDO 0.285 0.571 0.0

OBO Score Summary

count mean std min 25% 50% 75% max
score 1.0 0.285 NaN 0.285 0.285 0.285 0.285 0.285
score_dash 1.0 0.571 NaN 0.571 0.571 0.571 0.571 0.571
score_impact 1.0 0.000 NaN 0.000 0.000 0.000 0.000 0.000

OBO dependency graph